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cs.CV2026
Motion-Adapter: A Diffusion Model Adapter for Text-to-Motion Generation of Compound Actions
Yue Jiang, Mingyu Yang, Liuyuxin Yang +3
Recent advances in generative motion synthesis have enabled the production of realistic human motions from diverse input modalities. However, synthesizing compound actions from tex…
cs.CV2025
CEIDM: A Controlled Entity and Interaction Diffusion Model for Enhanced Text-to-Image Generation
Mingyue Yang, Dianxi Shi, Jialu Zhou +4
In Text-to-Image (T2I) generation, the complexity of entities and their intricate interactions pose a significant challenge for T2I method based on diffusion model: how to effectiv…
cs.CV2025
Dynamic Embedding of Hierarchical Visual Features for Efficient Vision-Language Fine-Tuning
Xinyu Wei, Guoli Yang, Jialu Zhou +4
Large Vision-Language Models (LVLMs) commonly follow a paradigm that projects visual features and then concatenates them with text tokens to form a unified sequence input for Large…